code: def forward(self, x):
      return self.model(x)
  
imports: from __future__ import annotations
  import pytorch_lightning
  import torch
  import torch.nn.functional
  from torch.optim.lr_scheduler import ExponentialLR
  from torch.utils.data import random_split, DataLoader
  from torchmetrics.functional import accuracy
  from torchvision.datasets import MNIST
  from torchvision import transforms
  import nni
  from .simple_torch_model import SimpleTorchModel
label_desc: Use image node_id 2 for calling the SimpleLightningModel obj's underlying member method code with example usage: obj.forward(x) and returns: self